In order to appropriately record or otherwise process streaming frames, such as by capturing streaming video frames, a number of control algorithms are implemented. For example, control algorithms for streaming frames include an automatic exposure control (AEC) algorithm, an automatic white balance (AWB) algorithm, a contrast optimization algorithm as described by U.S. Pat. No. 7,835,588 and the like. By way of example, the AEC algorithm receives information regarding the exposure and other image statistics relating to the current frame, determines whether the image represented by the current frame is underexposed, overexposed or properly exposed and, in an instance in which the image represented by the current frame is determined to be either underexposed or overexposed, suggests a different exposure for the next frame. In this regard, FIG. 1 depicts the illumination level of a plurality of frames with a solid line and, in turn, the exposure suggested by the AEC algorithm for the next frame with a dashed line. Because the analysis performed by the AEC algorithm is performed on a frame that has already been exposed, the illumination may change for the next frame. Since it is oftentimes desired that frames streaming experience no delay, there may be an occasional underexposure as represented by “u” in FIG. 1 or an occasional overexposure as represented by “o” in FIG. 1. Additionally, frequent changes in the exposure level, such as may be brought about from the analysis of the illumination level of the current frame, may generate repeated changes in the exposure level over the course of time in response to at least some relatively minor variations in image brightness such that the resulting visual effect may be somewhat unsettling for a viewer.
One technique has been developed that saves the unfiltered control values, that is, the product of one or more control algorithms, that have been determined for a number of prior frames and then determines and utilizes a weighted average of the control values. However, the convergence speed of this technique is not easily and accurately tunable. Additionally, the strength of the filtering provided by this technique may only be increased in an instance in which the number of samples that are saved is relatively high, which may also be disadvantageous.